Evidence map›Paper›PMID 35755167›Full record

ArticleJournal of immunology research2022

Prediction of Immune Infiltration Diagnostic Gene Biomarkers in Kawasaki Disease.

Hongjun Ba, Yao Wang, Lili Zhang, Huishen Wang, Zhan-Peng Huang, Youzhen Qin

Open access · goldAbstract read
In one paragraph

Article in Journal of immunology research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Hongjun BaDepartment of Paediatric Cardiology, Heart Centre, First Affiliated Hospital of Sun Yat-Sen University, 58# Zhongshan Road 2, Guangzhou 510080, China.ORCID https://orcid.org/0000-0001-5268-211X
Yao WangGuangzhou Medical University Cancer Hospital, Guangzhou 510095, China.ORCID https://orcid.org/0000-0002-0696-3735
Lili ZhangDepartment of Paediatric Cardiology, Heart Centre, First Affiliated Hospital of Sun Yat-Sen University, 58# Zhongshan Road 2, Guangzhou 510080, China.ORCID https://orcid.org/0000-0003-4902-7522
Huishen WangDepartment of Paediatric Cardiology, Heart Centre, First Affiliated Hospital of Sun Yat-Sen University, 58# Zhongshan Road 2, Guangzhou 510080, China.ORCID https://orcid.org/0000-0001-6869-4473
Zhan-Peng HuangKey Laboratory on Assisted Circulation, Ministry of Health, 58# Zhongshan Road 2, Guangzhou 510080, China.ORCID https://orcid.org/0000-0001-7054-655X
Youzhen QinDepartment of Paediatric Cardiology, Heart Centre, First Affiliated Hospital of Sun Yat-Sen University, 58# Zhongshan Road 2, Guangzhou 510080, China.ORCID https://orcid.org/0000-0003-3097-9216
Sun Yat-sen University · CNGuangzhou Medical University Cancer Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Kawasaki disease (KD) is characterized by disorder of immune response with unknown etiology. Immune cells may be closely related to the onset of KD. The focus of this research was to evaluate the significance of the infiltration of immune cells for this disease and find possible diagnostic biomarkers for KD. The Gene Expression Omnibus database was utilized to retrieve two freely accessible gene expression patterns (GSE68004 and GSE18606 datasets) from human KD and control specimens. 114 KD, as well as 46 control specimens, were searched for obtaining differentially expressed genes (DEGs). Candidate biological markers were determined utilizing the support vector machine recursive feature elimination and the least absolute shrinkage and selection operator regression model analysis. To assess discriminating capacity, the area under the receiver operating characteristic curve (AUC) was computed. The GSE73461 dataset was utilized to observe the biomarkers' expression levels and diagnostic significance in KD (78 KD patients and 55 controls). CIBERSORT was employed to assess the composition profiles of the 22 subtypes of immune cell fraction in KD on the basis of combined cohorts. 37 genes were discovered. The DEGs identified were predominantly involved in arteriosclerotic cardiovascular disease, atherosclerosis, autoimmune disease of the urogenital tract, and bacterial infectious disease. Gene sets related to complement and coagulation cascades, Toll-like receptor signaling pathway, Fc gamma R-mediated phagocytosis, NOD-like receptor signaling pathway, and regulation of actin cytoskeleton underwent differential activation in KD as opposed to the controls. KD diagnostic biomarkers, including the alkaline phosphatase (ALPL), endoplasmic reticulum degradation-enhancing alpha-mannosidase-like protein 2 (EDEM2), and histone cluster 2 (HIST2H2BE), were discovered (AUC = 1.000) and verified utilizing the GSE73461 dataset (AUC = 1.000). Analyses of immune cell infiltration demonstrated that ALPL, EDEM2, and HIST2H2BE were linked to CD4 memory resting T cells, monocytes, M0 macrophages, CD8 T cells, neutrophils, and memory CD4 T cells. ALPL, EDEM2, and HIST2H2BE could be utilized as KD diagnostic indicators, and they can also deliver useful information for future research on the disease's incidence and molecular processes.

Indexed as

Mucocutaneous Lymph Node SyndromeBiomarkersHistonesHumansROC CurveSupport Vector MachineBiomarkersHistones

Identifiers

PMID35755167
PMCPMC9232301
OpenAlexW4283026370

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.